PyCharm Printing Numpy Arrays (IndexError: tuple index out of range) about yolov3

[glenn-jocher]

@CF2220160244 I get the same error on printing numpy arrays, but I think in my case this is a PyCharm problem. In PyCharm if I convert the numpy array to a torch tensor print works fine:

labels0 = np.loadtxt(label_path, dtype=np.float32).reshape(-1, 5)

print(labels0)
Traceback (most recent call last):
...
IndexError: tuple index out of range

print(torch.from_numpy(labels0))
tensor([[76.00000,  0.35609,  0.44456,  0.54970,  0.16180],
        [ 0.00000,  0.48129,  0.40587,  0.94952,  0.80312]])

In Spyder the same operation shows no errors:

ipdb> labels0 = np.loadtxt(label_path, dtype=np.float32).reshape(-1, 5)

ipdb> labels0
array([[76.      ,  0.356086,  0.444563,  0.549703,  0.161803],
       [ 0.      ,  0.481289,  0.405874,  0.949516,  0.803123]], dtype=float32)

ipdb> print(labels0)
[[76.        0.356086  0.444563  0.549703  0.161803]
 [ 0.        0.481289  0.405874  0.949516  0.803123]]

[simedw]

The issue seem to be that the print option for float_kind has a typo (https://github.com/ultralytics/yolov3/blob/master/utils/utils.py#L10).
Try changing
np.set_printoptions(linewidth=320, formatter={'float_kind': '{11.5g}'.format})
to
np.set_printoptions(linewidth=320, formatter={'float_kind': '{:11.5g}'.format})
(format was trying to access the 11th element of the input instead of using 11.5g as formatting)

[glenn-jocher]

@simedw you are right, this fixes the problem! I implemented this change in commit bce94f6.

[NaumanKhan665]

@simedw you are right, this fixes the problem! I implemented this change in commit bce94f6.
But this error is not fixed by using th above suggestion
return a.reshape((1, a.shape[0], a.shape[1]))
IndexError: tuple index out of range

[glenn-jocher]

@NaumanKhan665
Hello, thank you for your interest in our work! Please note that most technical problems are due to:

• Your changes to the default repository. If your issue is not reproducible in a fresh git clone version of this repository we can not debug it. Before going further run this code and ensure your issue persists:

sudo rm -rf yolov3  # remove exising repo
git clone https://github.com/ultralytics/yolov3 && cd yolov3 # git clone latest
python3 detect.py  # verify detection
python3 train.py  # verify training (a few batches only)
# CODE TO REPRODUCE YOUR ISSUE HERE

• Your custom data. If your issue is not reproducible with COCO data we can not debug it. Visit our Custom Training Tutorial for exact details on how to format your custom data. Examine train_batch0.jpg and test_batch0.jpg for a sanity check of training and testing data.
• Your environment. If your issue is not reproducible in a GCP Quickstart Guide VM we can not debug it. Ensure you meet the requirements specified in the README: Unix, MacOS, or Windows with Python >= 3.7, Pytorch >= 1.1, etc. You can also use our Google Colab Notebook to test your code in working environment.

If none of these apply to you, we suggest you close this issue and raise a new one using the Bug Report template, providing screenshots and minimum viable code to reproduce your issue. Thank you!